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research at the intersection of quantum information science and fundamental materials science focused on understanding the coherent dynamics of optically accessible spins in bulk and van der Waals materials
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computed tomography (CT) reconstruction, including sparse-view and limited-angle algorithms, and the application of advanced machine learning (ML) and computational imaging methods to scientific and
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acquisition conditions in real time (drift correction, autofocus) for efficient atomic-resolution STEM-EDS/EELS spectrum imaging Develop AI-enabled approaches for multi-modal electron tomography acquisition and
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and validating scattering‑correction and calibration workflows that yield quantitative attenuation coefficients, and (2) designing adaptive tomography approaches that reduce acquisition time while
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of irradiated materials using advanced techniques such as transmission and scanning electron microscopy, X-ray tomography, and related methods. Analyze experimental data to determine mechanisms of irradiation
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Advanced characterization skills such as optical and high-resolution electron microscopy (SEM, TEM, EBSD) Familiar with multi-axis robotic system and program Excellent record of productive and creative
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problems. Major Duties/Responsibilities: Perform processing and analysis on multimodal data streams, including RF, optical, and spectral signals Develop statistically defensible algorithms to identify and
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Preferred Qualifications: We are interested in candidates with general research experiences in quantum optics and quantum information science. Priority is given to candidates with experience on the design
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the functional properties of novel ferroic material systems and correlate their nanoscale ferroelectric, ferroelastic, optical, and electrical responses with structure and environment, with relevance
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out experiments exploring the dynamics of high-intensity beams in the SNS ring. This project will explore a unique space charge mitigation technique based on coupled optics and phase space painting